Board FAQ
Questions nominating committees ask me about AI oversight. Answered plainly.
Why an operator instead of a career director?
Career directors bring governance process. I bring the process and the scar tissue. I’ve run technology programs inside large companies for 23 years, which means I’ve lived the decisions a board oversees: what to approve, what to kill, what to disclose. Oversight is sharper when you’ve sat on the other side of it.
What does AI oversight actually require from a board?
Not technical expertise. The right questions, asked consistently. Where does our AI touch customer data, and who approved that boundary? What happens when the model is wrong, and who is accountable that day? Which AI workloads did we say no to this year, and why? A board that asks those questions governs AI just fine.
How does AI risk touch fiduciary duty?
The same way any operational risk does. If AI makes decisions about customers, employees, or money, the board needs to know the controls exist and who owns them. You don’t need to understand the model. You need to understand the accountability chain.
What’s the time commitment?
Standard board and committee cadence. I take on a small number of board roles and give each one real attention. If I can’t do the job properly, I won’t take the seat.
Won’t you just push your own AI agenda?
No. The core of my position is knowing when AI isn’t the answer. I’ve killed more AI use cases than I’ve championed. A board needs someone who will say “don’t build this” as readily as “build this.”
What do you actually do in the boardroom?
Ask the questions management isn’t asking itself. Translate vendor promises into plain language. Pressure-test the AI roadmap against the reality of the data estate. And keep one uncomfortable question on the table: should this be AI at all?